Statistical Analysis of QTL Crosses and Gene Expression Arrays This project will apply newly developed statistical methods to experimental data obtained form rodent models of hypertension in order to identify genes and pathways that underlie blood pressure regulation in mammals. The first component, quantitative trait locus (QTL) mapping, will identify polymorphic loci that affect blood pressure in rodents. Epistasis analysis will be used to identify loci that participate in common biochemical pathways. The second component, gene expression microarray analysis, will identify changes in the expression of genes in tissue samples. The analysis of expression data will identify the downstream consequences of allelic variation at both QTL and candidate genes. The combination of a phenotype driven approach, QTL mapping, with a gene driven approach, expression analysis, will allow us to identify and characterize the effects of allelic variations that lead to hypertension. Our analyses of these two types of data will generate testable hypotheses about specific genes and pathways related to hypertension in rodents that can then be extended to human hypertension.